Data Scientist

Description

Job Overview
Do you want to uncover hidden insights from data and use those to drive decisions and influence behavior to create business value for our clients If so, the Analytics Practice within the Conduent Technology innovation (CTI) organiation has an exciting opportunity for you. The CTI Analytics team works closely with Conduent business groups to address real world challenges such as the rising cost of healthcare, mobility in urban society and payment card fraud in financial welfare programs, using the power of Data Analytics. We adopt a multidisciplinary approach that combines techniques from diverse domains such as data mining and machine learning, statistical modeling, simuation, optimization and multimedia analysis, and use big data technologies to consolidate and analyze volumes of data from multiple sources in a scalable manner. We are looking for data scientists to work on machine learning, data mining, and statistical modeling for predictive and prescriptive enterprise analytics. Successful candidates will be expected to investigate state of the art techniques in advanced machine learning and statistical modeling, and design, develop, and deploy stateofart, scalable systems for innovative analytics applications in a set of industrial verticals (e.g. healthcare, transportation, customer care etc.). Applicants will be expected to work with a diverse set of data sources, such as time series data, spatial, graph data, semistructured and unstructured data, and build statistical/machinelearning models in support of ondemand, realtime analytic services. The applicant should also have strong skills in explaining and interpreting the analytic models and outcomes in both research and application contexts.
Responsibilities
Research, design and prototype robust and scalable models based on machine learning, data mining, and statistical modeling to answer key business problems Build tools and support structures needed to analyze data, perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices Work with development teams & business groups to ensure models can be implemented as part of a delivered solution replicable across many clients
Present findings to stakeholders to drive improvements and solutions from concept through to delivery
Keep abreast of the latest developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand
Collaborate closely with university partners and other scientists and engineers in a multidisciplinary work environment
Qualifications
PhD in computer science, computer engineering or MS with 5+ years of experience in related field. Demonstrated history of driving and delivering analytics models and solutions Deep knowledge of fundamentals of machine learning, data mining and statistical predictive modeling, and extensive experience applying these methods to real world problems
Strong skills in software prototyping and engineering with expertise in applicable programming and analytics languages (Python, R, C/C++) and various open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work
Desired interdisciplinary skills include big data technologies, ETL, statistics and causal inference, Deep Learning, modeling and simulation
Breadth of skills and experience in machine learning diverse types of data, diverse data sources, different types of learning models, diverse learning settings Ability and inclination to work in multidisciplinary environments, and desire to see ideas realized in practice
Experience and knowledge in services domains such as business process outsourcing systems, transportation systems, healthcare systems and financial services is valued
Demonstrated ability to propose novel solutions to problems, performing experiments to show feasibility of their solutions and working to refine the solutions into a realworld context
Strong analytical, written, and verbal communication skills